The subfield of molecular diagnostics which relates to nucleic acid quantitation has embraced kinetic analysis as a means for interpreting results from nucleic acid amplification reactions. In these procedures, sometimes referred to as “real-time” amplification procedures, the amount of amplicon present in a nucleic acid amplification reaction mixture is monitored as a function of time. Ideally, the result of this monitoring is a growth curve having a sigmoid shape, where an initial baseline phase is followed by a growth phase, which is followed by a plateau phase.
Another important trend in the molecular diagnostics field is the drive toward full automation of laboratory procedures and analysis of results. Fully automated real-time nucleic acid assays require machine executable algorithms capable of analyzing data. In this regard, there is a requirement for data processing algorithms that accurately output an amount or concentration of a nucleic acid that gave rise to an observed amplification result.
Prior methods of automating the analysis of real-time amplification reactions have relied on mathematical treatments of growth curves. For example, certain algorithms are based on the slope of the log-linear segment of a growth curve, or on derivative-based analysis of most or all of the curve. Frequently, there is an additional requirement for calculating a “threshold” value which must be exceeded to indicate a true positive amplification result.
Unfortunately, the quantitative abilities of some prior methods for analyzing results from real-time nucleic acid amplification reactions are compromised at very low target levels (i.e., less than about 100 copies/reaction). This may be due to a fanning pattern which characterizes growth curves of reactions conducted using very low target levels, meaning that different reactions conducted using presumably identical initial target amounts produce amplicons at somewhat different rates. Stated differently, the kinetics of amplification in reactions conducted using very low template levels exhibit noticeable fluctuation, and this fluctuation leads to uncertainty in the final quantitative result generated by some algorithms. Methods that additionally require calculation of a threshold for indicating a positive result compound this uncertainty.
Thus, there exists a need for quantitative methods which are not severely compromised by problems related to fluctuation in data derived from real-time amplification of low levels of target.